The 1st EAI International Conference on Smart Grid Assisted Internet of Things

Research Article

Collaborative detection and response framework against SQL injection attacks in IoT-based smart grids

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  • @INPROCEEDINGS{10.4108/eai.7-8-2017.152986,
        author={Chahira Boukhari and Abdelouahid Derhab and Mohamed Guerroumi and Nadia Nouali and Abdelaziz Babakhouya and Abdelkarim Meziane},
        title={Collaborative detection and response framework against SQL injection attacks in IoT-based smart grids},
        proceedings={The 1st EAI International Conference on Smart Grid Assisted Internet of Things},
        publisher={EAI},
        proceedings_a={SGIOT},
        year={2017},
        month={8},
        keywords={IoT-based Smart grid SQL injection log le collaborative detection.},
        doi={10.4108/eai.7-8-2017.152986}
    }
    
  • Chahira Boukhari
    Abdelouahid Derhab
    Mohamed Guerroumi
    Nadia Nouali
    Abdelaziz Babakhouya
    Abdelkarim Meziane
    Year: 2017
    Collaborative detection and response framework against SQL injection attacks in IoT-based smart grids
    SGIOT
    EAI
    DOI: 10.4108/eai.7-8-2017.152986
Chahira Boukhari1,*, Abdelouahid Derhab2,3, Mohamed Guerroumi4, Nadia Nouali1, Abdelaziz Babakhouya1, Abdelkarim Meziane1
  • 1: Research Center for Scienti c and Technical Information, Algeria.
  • 2: Center of Excellence in Information Assurance, King Saud University,
  • 3: Saudi Arabia.
  • 4: USTHB University, Algeria
*Contact email: boukhari.chahira@gmail.com

Abstract

In this paper, we propose a collaborative detection and response framework against SQL injection attacks in IoT-based smart grids. The framework is composed of a set of host-based detection systems; each of which is deployed at a smart meter, in addition, at the data management server. When an attack at one host is detected, the network administrator is noti ed and remotely patches the other hosts. The detection engine is lightweight as each smart meters analyzes the log le associated with its network traffic. Hence, the framework is sacalable to large IoT-based smart grids as the detection task is performed by each smart meter and does not rely on a single component. Prelimary results are promising in terms of true positive and false positive rates.